Please use this identifier to cite or link to this item:
http://publications.jrc.ec.europa.eu/repository/handle/JRC72736

Full metadata record

DC Field

Value

Language

dc.contributor.author

NORLEN Hedvig

en_GB

dc.contributor.author

BERGGREN Katarina

en_GB

dc.contributor.author

WHELAN Maurice

en_GB

dc.contributor.author

WORTH Andrew

en_GB

dc.date.accessioned

2014-03-27T01:02:49Z

-

dc.date.available

2012-12-31

en_GB

dc.date.available

2014-03-27T01:02:49Z

-

dc.date.created

2012-10-30

en_GB

dc.date.issued

2012

en_GB

dc.date.submitted

2012-07-04

en_GB

dc.identifier.isbn

978-92-79-26058-2 (print)

en_GB

dc.identifier.isbn

978-92-79-21708-1 (pdf)

en_GB

dc.identifier.issn

1018-5593 (print)

en_GB

dc.identifier.issn

1831-9424 (online)

en_GB

dc.identifier.other

EUR 25473 EN

en_GB

dc.identifier.other

OPOCE LB-NA-25473-EN-C (print); LB-NA-25473-EN-N (online)

en_GB

dc.identifier.uri

http://publications.jrc.ec.europa.eu/repository/handle/JRC72736

-

dc.description.abstract

We have assessed the abilities of five alternative (non-animal) approaches to predict acute oral toxicity, a toxicological endpoint relevant to multiple pieces of legislation on chemicals and consumer products. In particular, we have investigated four QSAR models (ToxSuite, TOPKAT, TEST and ADMET Predictor) and one in vitro method (3T3 NRU). Based on a test set of in vitro and in vivo data for 180 compounds, we have characterized the predictive performance of each method when used alone (both for LD50 prediction and acute toxicity classification into three categories), as well as multiple test combinations (batteries) and stepwise testing strategies (for acute toxicity classification into three categories). When used individually, the alternative methods showed an ability to predict LD50 with correlation coefficients in the range from 49% to 84%, and to classify into three toxicity groups with accuracies in the range from 41% to 72%. When the alternative methods were combined into batteries or testing strategies, the overall accuracy of prediction could reach 76%. We also illustrate how different combinations of methods can be used to optimize sensitivity or specificity.

en_GB

dc.description.sponsorship

JRC.I.5-Systems Toxicology

en_GB

dc.format.medium

Printed

en_GB

dc.language

ENG

en_GB

dc.publisher

Publications Office of the European Union

en_GB

dc.relation.ispartofseries

JRC72736

en_GB

dc.title

An investigation into the use of computational and in vitro methods for acute systemic toxicity prediction